EC2 (Un)Problematic Bias.
Another challenge is determining whether a high correlation value actually corresponds to problematic bias [1]}, [2]}.
Decision makers need to evaluate whether they think a certain bias reflects their intentions with the neural network, or if corrections need to be made [3]}.
This subjective assessment of separating problematic from non-problematic bias is ultimately left to human evaluation in the data and modeling process.
Nonetheless, it should be supported by bias visualization approaches for large label spaces.
While this challenge also exists for other fairness visualization approaches, it needs to be tailored to our setting of comparing a large label space with specific sensitive attributes.
